BUEC 232 Lecture Notes - Lecture 10: Probability Distribution, Random Variable, Probability Plot

• School: Simon Fraser University
• Department: Business Administration and Economics
• Course: BUEC 232
• Professor: bisher

Document Summary

Discrete probability distributions, please arra(cid:374)ge yourselves i(cid:374) pairs for to(cid:374)ight(cid:859)s le(cid:272)ture, data and decisions 1, week 5 course feedback request, lectures are on track with course syllabus, midterm covering ch. 1-4 & l1-l8 on february 22: hypergeometric distribution. Applies to sampling without replacement from a finite population whose elements can be classified into two mutually exclusive categories. (e. g. pulling multiple cards from a single standard deck. ) Each trial has exactly two mutually exclusive outcomes: a fixed number of trials, n, unlike binomial in that: The trials are (cid:374)ot i(cid:374)depe(cid:374)de(cid:374)t as ea(cid:272)h su(cid:272)(cid:272)ess depletes a fi(cid:374)ite pool of (cid:862)su(cid:272)(cid:272)esses(cid:863): hypergeometric probability distribution formula, hypergeometric distribution characteristics. These can potentially take on any degree of precision, depending only on the ability to measure: ofte(cid:374) they are (cid:862)dis(cid:272)retized(cid:863) (cid:271)y assig(cid:374)i(cid:374)g the(cid:373) i(cid:374)to u(cid:374)ifor(cid:373) ra(cid:374)ges. (i. e. income measured in. Symmetrical so mean, median and mode are equal. Spread is determined by the standard deviation, .